title: Impact of schedule duration on head and neck radiotherapy: accelerated tumor repopulation versus compensatory mucosal proliferation.
abstract: OBJECTIVE
  To determine how modelled maximum tumor control rates, achievable without exceeding mucositis tolerance (tcp(max-early)) vary with schedule duration for head and neck squamous cell carcinoma (HNSCC).
  
  
  METHODS
  Using maximum-likelihood techniques, we have fitted a range of tcp models to two HNSCC datasets (Withers' and British Institute of Radiology [BIR]), characterizing the dependence of tcp on duration and equivalent dose in 2 Gy fractions (EQD(2)). Models likely to best describe future data have been selected using the Akaike information criterion (AIC) and its quasi-AIC extension to overdispersed data. Setting EQD(2)s in the selected tcp models to levels just tolerable for mucositis, we have plotted tcp(max-early) against schedule duration.
  
  
  RESULTS
  While BIR dataset tcp fits describe dose levels isoeffective for tumor control as rising significantly with schedule protraction, indicative of accelerated tumor repopulation, repopulation terms in fits to Withers' dataset do not reach significance after accounting for overdispersion of the data. The tcp(max-early) curves calculated from tcp fits to the overall Withers' and BIR datasets rise by 8% and 0-4%, respectively, between 20 and 50 days duration; likewise, tcp(max-early) curves calculated for stage-specific cohorts also generally rise slowly with increasing duration. However none of the increases in tcp(max-early) calculated from the overall or stage-specific fits reach significance.
  
  
  CONCLUSIONS
  Local control rates modeled for treatments which lie just within mucosal tolerance rise slowly but insignificantly with increasing schedule length. This finding suggests that whereas useful gains may be made by accelerating unnecessarily slow schedules until they approach early reaction tolerance, little is achieved by shortening schedules further while reducing doses to remain within mucosal tolerance, an approach that may slightly worsen outcomes.
authors.affiliation: School of Cancer Studies, University of Liverpool, Liverpool L69 3GA, United Kingdom. john.fenwick@rob.ox.ac.uk
authors.forename: John D
authors.initials: JD
authors.lastname: Fenwick
authors.forename: Juan
authors.initials: J
authors.lastname: Pardo-Montero
authors.forename: Alan E
authors.initials: AE
authors.lastname: Nahum
authors.forename: Zafar I
authors.initials: ZI
authors.lastname: Malik
mesh_terms: D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000473:pathology / Q000532:radiotherapy*; D049109:Cell Proliferation / Q000528:radiation effects*; D019583:Dose Fractionation, Radiation; D006258:Head and Neck Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D006801:Humans; D016013:Likelihood Functions; D008962:Models, Theoretical; D009061:Mouth Mucosa / Q000473:pathology / Q000528:radiation effects*; D009367:Neoplasm Staging; D011832:Radiation Injuries / Q000473:pathology*; D011836:Radiation Tolerance / Q000502:physiology*; D012062:Relative Biological Effectiveness; D013280:Stomatitis / Q000473:pathology; D013997:Time Factors